1. Technical Field
The present invention relates to computer graphics and more particularly, to texturing three-dimensional (3D) models with two-dimensional (2D) images.
2. Discussion of the Related Art
Texture mapping has been a fundamental issue in computer graphics from its early days. As online image databases have become increasingly accessible, the ability to texture 3D models using casual 2D images has gained importance. This will facilitate, for example, the task of texturing models of an animal using any of the hundreds of images of this animal found on the Internet, or enabling a naive user to create personal avatars using the user's own images. To texture a model using an image, a mapping from the surface to the image should be calculated. Given user-defined constraints, a common approach to establish this mapping is employing constrained parameterization. This approach computes the mapping by embedding the mesh onto the image plane, while attempting to satisfy the constraints and minimize a specific distortion metric. This approach is suitable for casual images, since no prior assumptions regarding the source image and the camera are made. However, inherent distortions might be introduced due to photography effects that result from the viewpoint and the object's 3D geometry.
FIG. 1 illustrates the aforementioned aspect of the existing art. A 3D mesh 11 representing a cylinder is provided together with a 2D image 12 containing a textured cylinder. Specifically, in image 12, the text appears curved and the squares in the center seem wider than those near the silhouettes. These photography effects result from the viewpoint and the object's 3D geometry. In mesh 11, a cylinder with different proportions is being used. Several pairs of constraints 11A/12A-11F/12F are specified thus geometrically associating mesh 11 with image 12. Both mesh 11 and image 12 are then fed into constrained parameterization texturing system 10 which yield a textured mesh 13. It is clearly shown from textured mesh 13 that the texture is distorted due to the dissimilarity in the shape of the cylinder of mesh 11 and the cylinder of image 12, as well as the different orientation of the cameras. Even when using a large number of constraints, constrained parameterization cannot produce a satisfactory mapping, since its two goals—minimizing distortions and satisfying constraints conflict.
If the cylinder of mesh 11 and the cylinder of image 12 were highly similar, a photogrammetric approach could solve the aforementioned distortion, by recovering the camera's parameters. Using these parameters to re-project the mesh 11 onto the image 12 would compensate for the photography effects. However, since mesh 11 and image 12 represent a-similar objects, the photogrammetric approach cannot be used.